An informatics software stack for point defect-derived opto-electronic properties: the Asphalt Project

Computational acceleration of performance metric-based materials discovery via high-throughput screening and machine learning methods is becoming widespread. Nevertheless, development and optimization of the opto-electronic properties that depend on dilute concentrations of point defects in new mate...

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Bibliographic Details
Published in:MRS communications 2019-09, Vol.9 (3), p.839-845
Main Authors: Baker, Jonathon N., Bowes, Preston C., Harris, Joshua S., Irving, Douglas L.
Format: Article
Language:English
Subjects:
Acceleration
Algorithms
Artificial Intelligence Prospective
Artificial Intelligence Prospectives
Asphalt
Biomaterials
Characterization and Evaluation of Materials
Computer simulation
Design
First principles
Genomes
Informatics
Machine learning
Materials Engineering
Materials Science
Nanotechnology
Optimization
Optoelectronics
Point defects
Polymer Sciences
Thermodynamics
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Summary:Computational acceleration of performance metric-based materials discovery via high-throughput screening and machine learning methods is becoming widespread. Nevertheless, development and optimization of the opto-electronic properties that depend on dilute concentrations of point defects in new materials have not significantly benefited from these advances. Here, the authors present an informatics and simulation suite to computationally accelerate these processes. This will enable faster and more fundamental materials research, and reduce the cost and time associated with the materials development cycle. Analogous to the new avenues enabled by current first-principles-based property databases, this type of framework will open entire new research frontiers as it proliferates.
ISSN:2159-6859
2159-6867
DOI:10.1557/mrc.2019.106